Metabolic profiles characterizing different phenotypes of polycystic ovary syndrome: plasma metabolomics analysis

Follicular fluid lipidomic profiling reveals potential biomarkers of polycystic ovary syndrome: A pilot study

BACKGROUND

Polycystic ovary syndrome (PCOS) is a heterogeneous endocrine disorder associated with multiple metabolic conditions including obesity, insulin resistance, and dyslipidemia. PCOS is the most common cause of anovulatory infertility; however, the molecular diversity of the ovarian follicle microenvironment is not fully understood. This study aimed to investigate the follicular fluid (FF) lipidomic profiles in different phenotypes of PCOS and to explore novel lipid biomarkers.

METHODS

A total of 25 women with PCOS and 12 women without PCOS who underwent in vitro fertilization and embryo transfer were recruited, and their FF samples were collected for the lipidomic study. Liquid chromatography-tandem mass spectrometry was used to compare the differential abundance of FF lipids between patients with different PCOS phenotypes and controls. Subsequently, correlations between specific lipid concentrations in FF and high-quality embryo rate (HQER) were analyzed to further evaluate the potential interferences of lipid levels with oocyte quality in PCOS. Candidate biomarkers were then compared via receiver operating characteristic (ROC) curve analysis.

RESULTS

In total, 19 lipids were identified in ovarian FF. Of these, the concentrations of ceramide (Cer) and free fatty acids (FFA) in FF were significantly increased, whereas those of lysophosphatidylglycerol (LPG) were reduced in women with PCOS compared to controls, especially in obese and insulin-resistant groups. In addition, six subclasses of ceramide, FFA, and LPG were correlated with oocyte quality. Twenty-three lipid subclasses were identified as potential biomarkers of PCOS, and ROC analysis indicated the prognostic value of Cer,36:1;2, FFA C14:1, and LPG,18:0 on HQER in patients with PCOS.

CONCLUSIONS

Our study showed the unique lipidomic profiles in FF from women with PCOS. Moreover, it provided metabolic signatures as well as candidate biomarkers that help to better understand the pathogenesis of PCOS.

Abnormal Activation of Tryptophan-Kynurenine Pathway in Women With Polycystic Ovary Syndrome

BACKGROUND

Women with polycystic ovary syndrome (PCOS) suffer from dysfunctional metabolism and studies have reported increased levels of tryptophan in patients with PCOS. However, the changes of downstream metabolites in tryptophan catabolism pathways remain unclear.

METHODS

This is a cross-sectional study that included 200 PCOS patients and 200 control women who were recruited from the Reproductive Medicine Center of Peking University Third Hospital from October 2017 to June 2019. The PCOS patients and the control group were further divided into subtypes of normal weight and overweight/obesity. Fasting blood samples from all subjects were collected on days 2~3 of a natural menstrual cycle or when amenorrhea for over 40 days with follicle diameter not exceeding 10 mm. The plasma levels of tryptophan metabolites were quantitatively determined by the liquid chromatograph mass spectrometer, including tryptophan, serotonin, kynurenine, kynurenic acid, 3-hydroxykynurenine, and quinolinic acid.

RESULTS

The tryptophan-kynurenine pathway was dysregulated in women with PCOS, along with significantly elevated levels of tryptophan, serotonin, kynurenine, kynurenic acid, and quinolinic acid. Moreover, levels of tryptophan, kynurenine, and kynurenic acid were positively correlated with luteinizing hormone, anti-Müllerian hormone, fasting insulin, HOMA-IR. tryptophan, and kynurenine and quinolinic acid had an obvious association with C-reactive protein levels. Furthermore, logistic regression showed that tryptophan, serotonin, kynurenine, kynurenic acid and quinolinic acid were all associated significantly with the increased risk of PCOS with the adjustment for potential confounding factors. Additionally, tryptophan, kynurenine, and kynurenic acid had good diagnostic performances for PCOS, and their combination exhibited higher sensitivity and specificity to diagnostic efficiency, with the area under the ROC curve of 0.824 (95% CI 0.777-0.871), which was comparable to the endocrine indicators.

CONCLUSION S

The tryptophan-kynurenine pathway was abnormally activated in PCOS patients.

Metabolic Syndrome and PCOS: Pathogenesis and the Role of Metabolites

Polycystic ovary syndrome (PCOS) is one of the most common endocrine diseases among women of reproductive age and is associated with many metabolic manifestations, such as obesity, insulin resistance (IR) and hyperandrogenism. The underlying pathogenesis of these metabolic symptoms has not yet been fully elucidated. With the application of metabolomics techniques, a variety of metabolite changes have been observed in the serum and follicular fluid (FF) of PCOS patients and animal models. Changes in metabolites result from the daily diet and occur during uncommon physiological routines. However, some of these metabolite changes may provide evidence to explain possible mechanisms and new approaches for prevention and therapy. This article reviews the pathogenesis of PCOS metabolic symptoms and the relationship between metabolites and the pathophysiology of PCOS. Furthermore, the potential clinical application of some specific metabolites will be discussed.

Metabolomics as a potential tool for the diagnosis of growth hormone deficiency (GHD): a review

Metabolomics uses several analytical tools to identify the chemical diversity of metabolites present in organisms. These metabolites are low molecular weight molecules (<1500 Da) classified as a final or intermediary product of metabolic processes. The application of this omics technology has become prominent in inferring physiological conditions through reporting on the phenotypic state; therefore, the introduction of metabolomics into clinical studies has been growing in recent years due to its efficiency in discriminating pathophysiological states. Regarding endocrine diseases, there is a great interest in verifying comprehensive and individualized physiological scenarios, in particular for growth hormone deficiency (GHD). The current GHD diagnostic tests are laborious and invasive and there is no exam with ideal reproducibility and sensitivity for diagnosis neither standard GH cut-off point. Therefore, this review was focussed on articles that applied metabolomics in the search for new biomarkers for GHD. The present work shows that the applications of metabolomics in GHD are still limited, since the little complementarily of analytical techniques, a low number of samples, GHD combined to other deficiencies, and idiopathic diagnosis shows a lack of progress. The results of the research are relevant and similar; however, their results do not provide an application for clinical practice due to the lack of multidisciplinary actions that would be needed to mediate the translation of the knowledge produced in the laboratory, if transferred to the medical setting.

Untargeted metabolomic approach to study the serum metabolites in women with polycystic ovary syndrome

BACKGROUND

Polycystic ovary syndrome (PCOS) is not only a kind of common endocrine syndrome but also a metabolic disorder, which harms the reproductive system and the whole body metabolism of the PCOS patients worldwide. In this study, we aimed to investigate the differences in serum metabolic profiles of the patients with PCOS compared to the healthy controls.

MATERIAL AND METHODS

31 PCOS patients and 31 matched healthy female controls were recruited in this study, the clinical characteristics data were recorded, the laboratory biochemical data were detected. Then, we utilized the metabolomics approach by UPLC-HRMS technology to study the serum metabolic changes between PCOS and controls.

RESULTS

The metabolomics analysis showed that there were 68 downregulated and 78 upregulated metabolites in PCOS patients serum compared to those in the controls. These metabolites mainly belong to triacylglycerols, glycerophosphocholines, acylcarnitines, diacylglycerols, peptides, amino acids, glycerophosphoethanolamines and fatty acid. Pathway analysis showed that these metabolites were enriched in pathways including glycerophospholipid metabolism, fatty acid degradation, fatty acid biosynthesis, ether lipid metabolism, etc. Diagnosis value assessed by ROC analysis showed that the changed metabolites, including Leu-Ala/Ile-Ala, 3-(4-Hydroxyphenyl) propionic acid, Ile-Val/Leu-Val, Gly-Val/Val-Gly, aspartic acid, DG(34:2)_DG(16:0/18:2), DG(34:1)_DG(16:0/18:1), Phe-Trp, DG(36:1)_DG(18:0/18:1), Leu-Leu/Leu-Ile, had higher AUC values, indicated a significant role in PCOS.

CONCLUSION

The present study characterized the difference of serum metabolites and related pathway profiles in PCOS patients, this finding hopes to provide potential metabolic markers for the prognosis and diagnosis of this disease.

Urinary Metabolites Reveal Hyperinsulinemia and Insulin Resistance in Polycystic Ovarian Syndrome (PCOS)

The identification of insulin resistance and hyperinsulinemia in polycystic ovary syndrome (PCOS) is not a minor issue. The homeostasis model assessment of insulin resistance index (HOMA) is the most used index of IR (Insulin Resistance), validated in overweight and obese patients but not in normal-weight PCOS subjects, who can still present with increased insulin secretion by an oral glucose tolerance test (OGTT). The evaluation of insulin secretion and resistance represents a still unresolved problem. The aim of this study is to identify a possible yet noninvasive method to properly evaluate the insulin metabolism in young non-diabetic subjects. Girls aged 14–22 years, afferent to the center of Gynecological Diseases in Childhood and Adolescence of Cagliari (Italy), were screened for PCOS. A total of 42 subjects comprised the study group. Hormonal assays, OGTT, transabdominal (TA) or transvaginal (TV) US, and urine collection for ¹H-NMR analysis were assayed in the early follicular phase. A ¹H-NMR coupled multivariate statistical analysis was performed. The OPLS model indicated that the NMR profile of urine had a good fit and prediction ability for the AUC OGTT with R² = 0.813. Metabolomics can be a promising tool to the potential identification of biomarkers of an exaggerated insulin response to OGTT and can encourage substantial progress for a more accurate and early diagnosis in PCOS.

Serum Metabolomics in PCOS Women with Different Body Mass Index

Polycystic ovary syndrome (PCOS) is the most prevalent endocrine and metabolic disorder, affecting 5–10% of women of reproductive age. It results from complex environmental factors, genetic predisposition, hyperinsulinemia, hormonal imbalance, neuroendocrine abnormalities, chronic inflammation, and autoimmune disorders. PCOS impacts menstrual regularities, fertility, and dermatological complications, and may induce metabolic disturbances, diabetes, and coronary heart disease. Comprehensive metabolic profiling of patients with PCOS may be a big step in understanding and treating the disease. The study aimed to search for potential differences in metabolites concentrations among women with PCOS according to different body mass index (BMI) in comparison to healthy controls. We used broad-spectrum targeted metabolomics to evaluate metabolites’ serum concentrations in PCOS patients and compared them with healthy controls. The measurements were performed using high-performance liquid chromatography coupled with the triple quadrupole tandem mass spectrometry technique, which has highly selective multiple reaction monitoring modes. The main differences were found in glycerophospholipid concentrations, with no specific tendency to up-or down-regulation. Insulin resistance and elevated body weight influence acylcarnitine C2 levels more than PCOS itself. Sphingomyelin (SM) C18:1 should be more intensively observed and examined in future studies and maybe serve as one of the PCOS biomarkers. No significant correlations were observed between anthropometric and hormonal parameters and metabolome results.

Metabolomic Biomarkers in Polycystic Ovary Syndrome: A Review of the Evidence

Polycystic ovary syndrome (PCOS) is an endocrinologic condition affecting one in five women of reproductive age. PCOS is often characterized by disruptions to the menstrual cycle, development of male-pattern hair growth (hirsutism), and polycystic ovary morphology. Recently, PCOS has been linked to metabolic dysfunction, with 40 to 80% of women characterized as overweight or obese. Despite these well-known negative health effects of PCOS, 75% of sufferers remain undiagnosed. This is most likely due to the variability in symptom presentation and the lack of a definitive test for the condition. Metabolomics, which is a platform used to analyze and characterize a large number of metabolites, has recently been proposed as a potential tool for investigating the metabolic pathways that could be involved in the pathophysiology of PCOS. In doing so, novel biomarkers could be identified to improve diagnosis and treatment of PCOS. This review aims to summarize the findings of recent metabolomic studies that highlight metabolic-specific molecules which are deranged in PCOS, to identify potential biomarkers for the condition. Current limitations for metabolomic studies are discussed, as well as future directions to progress the field toward further validation and integration into clinical practice.

Differences in gene expression of enzymes involved in branched-chain amino acid metabolism of abdominal subcutaneous adipose tissue between pregnant women with and without PCOS

OBJECTIVE

Polycystic ovary syndrome (PCOS) appears to be a common endocrine disorder of women in reproductive age. Adipose tissue (AT) is known as an active tissue in the metabolism of branched-chain amino acids (BCAA; Valine, Leucine, and Isoleucine) that they have associated with blood BCAA levels is a prognostic factor for insulin-resistant. Although the crucial roles of AT in women suffering from PCOS was reported, little information exists on the BCAA metabolism in AT of PCOS women. The aim was to assess and compare the expression of BCAAs metabolism pathway genes in abdominal subcutaneous AT of pregnant women with PCOS and non-PCOS pregnant women.

MATERIALS AND METHODS

AT samples from 13 PCOS were compared with samples collected from 6 non-PCOS women, all of whom underwent caesarean. Quantitative real-time PCR technique was used for gene expression of branched chain aminotransferase 2 mitochondrial (BCAT2), branched chain ketoacid dehydrogenase E1-alpha (BCKDHA), branched chain ketoacid dehydrogenase E1-Beta (BCKDHB), dihydrolipoamide branched chain transacylase E2 (DBT), dihydrolipoamide dehydrogenase E3 (DLD), branched chain ketoacid dehydrogenase kinase (BCKDK), Data were analyzed using t-test or U-test.

RESULTS

No significant differences were found in age and body mass index (BMI) between non-PCOS and PCOS women. The mRNA level of BCAT2 and DLD in PCOS group was not significantly different from non-PCOS group whereas mRNA level of BCKDHB and DBT was significantly increased in PCOS group (P < 0.0001). In contrast, mRNA level of BCKDHA (P = 0.0001) and BCKDK (P < 0.0001) was significantly decreased in PCOS group.

CONCLUSION

The alterations in gene expressions involved BCAA metabolism in age-matched and BMI- matched non-PCOS and PCOS pregnant women at delivery day was shown which warrants further studies regards functional activity. More attention should be given to AT of PCOS mothers that was previously ignored.

Raman spectroscopy of follicular fluid and plasma with machine-learning algorithms for polycystic ovary syndrome screening

Polycystic ovary syndrome (PCOS) is the main cause of anovulatory infertility and affects women throughout their lives. The specific diagnostic method is still under investigation. In the present study, we aimed to identify the metabolic tracks of the follicular fluid and plasma samples from women with PCOS by performing Raman spectroscopy with principal component analysis and spectral classification models. Follicular fluid and plasma samples obtained from 50 healthy (non-PCOS) and 50 PCOS women were collected and measured by Raman spectroscopy. Multivariate statistical methods and different machine-learning algorithms based on the Raman spectra were established to analyze the results. The principal component analysis of the Raman spectra showed differences in the follicular fluid between the non-PCOS and PCOS groups. The stacking classification models based on the k-nearest-neighbor, random forests and extreme gradient boosting algorithms yielded a higher accuracy of 89.32% by using follicular fluid than the accuracy of 74.78% obtained with plasma samples in classifying the spectra from the two groups. In this regard, PCOS may lead to the changes of metabolic profiles that can be detected by Raman spectroscopy. As a novel, rapid and affordable method, Raman spectroscopy combined with advanced machine-learning algorithms have potential to analyze and characterize patients with PCOS.

Gestational diabetes mellitus-associated changes in the breast milk metabolome alters the neonatal growth trajectory

BACKGROUND

Gestational diabetes mellitus (GDM) is the most common metabolic disturbance during pregnancy and leads to an altered metabolic profile of human breast milk (HBM). The association between HBM metabolites and neonatal growth in GDM pregnancies has not been thoroughly investigated.

AIMS

The primary aim was to quantify differences in the HBM metabolome between normal and GDM pregnancies. The secondary aim was to identify metabolites associated with neonatal growth during the first year postpartum.

METHODS

In the present study, mothers intending to exclusively breastfeed (BF) and their newborns (mother-infant pairs) were recruited at delivery (n = 129 normal pregnancies and n = 98 GDM pregnancies). HBM samples (colostrum, transition milk, and mature milk) from mothers with normal pregnancies (n = 50) and GDM pregnancies (n = 50) were subjected to metabolomic profiling via liquid chromatography tandem mass spectrometry (LC-MS/MS). Receiver operating characteristic (ROC) analysis revealed the metabolomic fingerprints of GDM-associated mature HBM. Correlations between metabolites and neonatal body weight gain (BWG) were evaluated by Spearman correlation analysis.

RESULTS

In total, 620 metabolites were identified in each HBM sample; 253 compounds had the same variation patterns, whereas 38 compounds had significantly different pattern transitions between the GDM and normal groups. Moreover, 12, 49 and 28 metabolites exhibited significant differences in the 3 milk types between the 2 groups. Twenty-two metabolites were confirmed by ROC analysis as metabolomic fingerprints in the mature BM of GDM patients. Ten compounds were significantly negatively correlated with neonatal growth, and only 2 unsaturated lipids (eicosatrienoic acid (FA 20:3) and lysophosphatidylcholine (LysoPC) (22:6)) were positively correlated with neonatal BWG.

CONCLUSIONS

GDM is associated with alterations in the HBM metabolome. Only a small subset of compounds are associated with neonatal body weight (BW).

TRIAL REGISTRATION

ChiCTR-ROC-17011508. Prospectively registered on 26 May 2017 (http://www.chictr.org.cn/listbycreater.aspx).

Potential effects of adropin on systemic metabolic and hormonal abnormalities in polycystic ovary syndrome

RESEARCH QUESTION

The study aimed to explore the effects of adropin on hormone concentrations and glucolipid and amino acid metabolism in patients with polycystic ovary syndrome (PCOS).

DESIGN

A total of 220 PCOS patients and 67 controls were recruited and basal state plasma was collected for adropin measurement. Follicular fluids from 50 PCOS patients and 30 controls were also collected for adropin analysis.

RESULTS

Plasma and follicular fluid adropin concentrations were lower in PCOS patients than controls (P < 0.001; P = 0.017). Adropin concentrations were negatively correlated with body mass index (BMI), free androgen index, Homeostatic Model Assessment of Insulin Resistance (HOMA-IR), androstenedione and triglycerides, and positively correlated with sex hormone-binding globulin (SHBG) and high-density lipoprotein (HDL) (all P < 0.05). PCOS patients who were either obese or glucose intolerant had lower adropin concentrations (P < 0.001). Follicular fluid adropin concentrations were negatively correlated with HOMA-IR, isoleucine and valine in the PCOS group (all P < 0.05). After adjusting for age, BMI, HOMA-IR and HDL, SHBG still significantly impacted the concentration of plasma adropin (P = 0.022). After adjusting for age and BMI, the odds of subjects with reduced adropin concentrations having PCOS still remained significant (P = 0.045). The association between plasma adropin and PCOS disappeared following SHBG adjustment.

CONCLUSIONS

The concentrations of adropin in plasma and follicular fluid were lower in PCOS patients, which might affect the development of insulin resistance. The association between adropin concentrations and hyperandrogenaemia in PCOS might be mediated through SHBG. The decreased adropin concentrations are associated with abnormal branched-chain amino acid metabolism in PCOS.

Intersection of Polycystic Ovary Syndrome and the Gut Microbiome

The etiology of polycystic ovary syndrome (PCOS) remains unclear, although studies indicate that both genetic and environmental factors contribute to the syndrome. In 2012, Tremellen and Pearce proposed the idea that dysbiosis of the intestinal (gut) microbiome is a causative factor of metabolic and reproductive manifestations of PCOS. In the past 5 years, studies in both humans and rodent models have demonstrated that changes in the taxonomic composition of gut bacteria are associated with PCOS. Studies have also clearly shown that these changes in gut microbiota are associated with PCOS as opposed to obesity, since these changes are observed in women with PCOS that are both of a normal weight or obese, as well as in adolescent girls with PCOS and obesity compared with body mass index- and age-matched females without the disorder. Additionally, studies in both women with PCOS and rodent models of PCOS demonstrated that hyperandrogenism is associated with gut microbial dysbiosis, indicating that androgens may modulate the gut microbial community in females. One study reported that the fecal microbiome transplantation of stool from women with PCOS or exposure to certain bacteria resulted in a PCOS-like phenotype in mice, while other studies showed that exposure to a healthy gut microbiome, pre/probiotics, or specific gut metabolites resulted in protection from developing PCOS-like traits in mice. Altogether, these results suggest that dysbiosis of the gut microbiome may be sufficient to develop PCOS-like symptoms and that modulation of the gut microbiome may be a potential therapeutic target for PCOS.

Correlation Between Serum Uric Acid and Body Fat Distribution in Patients With Polycystic Ovary Syndrome

OBJECTIVE

This study aims to investigate the correlation between serum uric acid levels and body fat distribution in patients with polycystic ovary syndrome (PCOS).

METHODS

Between May 2017 and March 2021, a total of 199 patients with PCOS were recruited from the Department of Endocrinology and Metabolism at the Shanghai Tenth People's Hospital. Anthropometric characteristics, metabolic parameters, and reproductive hormones were measured. Hyperuricemia was defined as serum uric acid (SUA) greater than 420 μmol/l. Dual-energy X-ray absorptiometry (DEXA) was used to measure body fat distribution.

RESULTS

The prevalence of hyperuricemia in patients with PCOS was 28.64%. PCOS patients with hyperuricemia are more obese and have a higher waist-to-hip ratio (WHR) and worse lipid metabolism than those without hyperuricemia. According to SUA quartiles, patients in the highest quartile had higher total testosterone (TT), body fat accumulation, and lower sex hormone-binding globulin (SHBG) than patients in the lowest quartile. SUA was correlated with percentage of total body fat, arm fat mass, leg fat mass, trunk fat mass, android/gynoid (A/G) ratio, and visceral adipose tissue (VAT) mass. After controlling possible confounders, logistic regression analysis found that only excessive VAT mass could significantly increase the risk of hyperuricemia in patients with PCOS.

CONCLUSION

In patients with PCOS, a high level of VAT mass, but not other fat compartments, will exacerbate the risk of hyperuricemia. Attention should be paid to the role of excessive VAT in the occurrence and development of PCOS with hyperuricemia.

Tailoring treatment for PCOS phenotypes

Introduction: Polycystic ovary syndrome (PCOS) is one of the most common endocrinopathies in reproductive-aged women. Hyperandrogenism, polycystic ovaries, chronic anovulation, and metabolic aberrations are its common features. The treatment approach focuses on the main aberrations, which characterize the different phenotypes. Areas covered: Management strategies targeting the metabolic phenotype include lifestyle modifications for weight loss and improvement of dietary habits, as well as medication, such as insulin-sensitizers. The treatment of hyperandrogenic phenotype includes cosmetic procedures and the combined oral contraceptives with or without antiandrogens. The therapeutic approach to reproductive phenotype includes diet and lifestyle modifications, clomiphene citrate, and aromatase inhibitors. Alternative treatments include dietary supplements, herbs, resveratrol, myo-inositol, and acupuncture. Expert opinion: New studies have shown that higher anti-Müllerian hormone levels, gut microbiome composition, and plasma metabolomics are new parameters that are related to the most severe phenotypes. The clinical phenotypes can change over the lifespan with weight gain and can coexist in the same individual. Individualized treatment remains the main approach but grouping the phenotypes and following therapeutic recommendations may prove to be also clinically appropriate.

Metabolomic Profiling of Pregnancies With Polycystic Ovary Syndrome Identifies a Unique Metabolic Signature and Potential Predictive Biomarkers of Low Birth Weight

BACKGROUND

Polycystic ovary syndrome (PCOS) is a complex syndrome with clinical features of an endocrine/metabolic disorder. Various metabolites show significant association with PCOS; however, studies comparing the metabolic profile of pregnant women with and without PCOS are lacking. In this study, metabolomics analysis of blood samples collected from PCOS women and age and BMI matched controls in the second trimester of pregnancy was performed to identify metabolic differences between the two groups and determine their association with pregnancy outcome.

METHODS

Sixteen PCOS and fifty-two healthy women in their second trimester underwent targeted metabolomics of plasma samples using tandem mass spectrometry with the Biocrates MxP^® Quant 500 Kit. Linear regression models were used to identify the metabolic alterations associated with PCOS, followed by enrichment and Receiver Operating Characteristic (ROC) analyses to determine the best indicators of pregnancy outcomes.

RESULTS

PCOS women had lower birth weight babies compared to healthy controls. As a group, systolic blood pressure (SBP) at both second trimester and at delivery negatively correlated with birth weight. Regression models indicated significant increases in the triglycerides C20:4_C34:3 and C18:2_C38:6 in the PCOS group [false discovery rate (FDR) <0.05]. Enrichment analysis revealed significant elevations in triglycerides containing arachidonic acid, linoleic acid and palmitic acid in the PCOS group. A number of indicators of baby birth weight were identified including SBP at delivery, hexosylceramide (d18:2/24:0), ceramide (d18.0/24.1) and serine, with an AUC for all predictors combined for low birth weight (≤2500grams) of 0.88 (95%CI: 0.75-1.005, p<0.001).

CONCLUSIONS

PCOS pregnancies resulted in babies with a lower birth weight, marked by a unique metabolic signature that was enriched with specific triglycerides and unsaturated fatty acids. The functional significance of these associations needs further investigation.

Association between circadian rhythm disruption and polycystic ovary syndrome

OBJECTIVE

To explore the association of circadian rhythm disruption with polycystic ovary syndrome (PCOS) and the potential underlying mechanism in ovarian granulosa cells (GCs).

DESIGN

Multicenter questionnaire-based survey, in vivo and ex vivo studies.

SETTING

Twelve hospitals in China, animal research center, and research laboratory of a women's hospital.

PATIENTS/ANIMALS

A total of 436 PCOS case subjects and 715 control subjects were recruited for the survey. In vivo and ex vivo studies were conducted in PCOS-model rats and on ovarian GCs collected from women with PCOS and control subjects.

INTERVENTION(S)

The PCOS rat model was established with the use of testosterone propionate.

MAIN OUTCOME MEASURE(S)

Assay for transposase-accessible chromatin with high-throughput sequencing (ATAC-seq), RNA sequencing, rhythmicity analysis, functional enrichment analysis.

RESULT(S)

There was a significant correlation between night shift work and PCOS. PCOS-model rats presented distinct differences in the circadian variation of corticotropin-releasing hormone, adrenocorticotropic hormone, prolactin, and a 4-h phase delay in thyrotropic hormone levels. The motif enrichment analysis of ATAC-seq revealed the absence of clock-related transcription factors in specific peaks of PCOS group, and RNA sequencing ex vivo at various time points over 24 hours demonstrated the differential rhythmic expression patterns of women with PCOS. Kyoto Encyclopedia of Genes and Genomes analysis further highlighted metabolic dysfunction, including both carbohydrate and amino acid metabolism and the tricarboxylic acid cycle.

CONCLUSION(S)

There is a significant association of night shift work with PCOS, and genome-wide chronodisruption exists in ovarian GCs.

Differences in fatty acid profiles and desaturation indices of abdominal subcutaneous adipose tissue between pregnant women with and without PCOS

The objective was to determine the differences in fatty acid (FA) profiles in subcutaneous adipose tissue (AT) between pregnant women with polycystic ovary syndrome (PCOS) and those without PCOS. FA profiles of AT samples from 13 PCOS and 32 non-PCOS, all of whom underwent caesarean section were compared using gas chromatography. Age and BMI in the two groups were similar. Twenty-one FAs were detected and the total saturated FA percentage of experimental groups was similar. While the total monounsaturated FA (MUFA) (p < 0.0004) and desaturase index (18:1 cis-9/18:0; p < 0.03) were higher in PCOS women than non-PCOS women, total polyunsaturated FA (PUFA) was lower in PCOS than non-PCOS women (p < 0.004). Docosahexaenoic acid level of the two groups was similar while α-linolenic acid and eicosapentaenoic acid levels were significantly (p < 0.05) lower in PCOS. Total trans-FA, C18:1 t9 and C18:2t were lower in PCOS women (p < 0.05). These results indicate differences in desaturase index, MUFA and PUFA, especially n-3 FA in AT between age and BMI-matched pregnant PCOS and non-PCOS pregnant subjects. Further studies are warranted to replicate these findings and to investigate potential changes in these profiles in non-pregnant PCOS women.

Polycystic ovary syndrome in adolescents: Q-TOF LC/MS analysis of human plasma metabolome

Polycystic ovary syndrome (PCOS) is a hormonal disorder common among women of reproductive age. Women with PCOS may have infrequent or prolonged menstrual periods or excess male hormone levels. Metabolomics provide information on early biochemical changes in patients. Our aim was to find potential biomarkers on metabolome level to notice PCOS in adolescents and propose treatment opportunities based on our findings on metabolome level. In this study, Q-TOF LC/MS based analysis of the plasma samples of 15 healthy adolescents as control group (Group C) were compared with the plasma samples of 15 adolescents having PCOS (Group T). Raw chromatograms were processed on XCMS using Isotopologue Parameter Optimization (IPO) to optimize XCMS parameters. Finally, 2288 peaks were found but 84 of them had fold changes >1.5 based on normalized peak areas and they were statistically different (p < 0.05) between the groups. These peaks were subjected to MetaboAnalyst 4.0 - MS Peaks to Pathways utility for putative identification. The final list based on putative identification were evaluated through a clinical perspective and the statistically proved variation on the metabolite profiles of Group T and Group C presented that PCOS directly affected the lipid metabolism in the body or occurred as a result of a deformation in the lipid metabolism. Lower amount of Gamma-Tocopherol and higher amount of Coenzyme Q9, which is a product of incomplete Coenzyme Q10 biosynthesis, in the plasma samples of adolescent PCOS patients encouraged us to suggest larger randomized placebo controlled studies for Gamma-Tocopherol and Coenzyme Q10 supplements on the disease situation since our findings on metabolome level were in an accordance with the previous clinical findings.

Metabolomics and correlation network analysis of follicular fluid reveals associations between l-tryptophan, l-tyrosine and polycystic ovary syndrome

Polycystic ovary syndrome (PCOS) is an endocrine and metabolic disorder in women of reproductive age. Some studies have investigated metabolic alterations in plasma and follicular fluid from PCOS patients, but they did not control for obesity or insulin resistance (IR); additionally, correlation analysis of metabolites is sparse. Accordingly, in this study, we aimed to examine metabolic differences owing to the pathogenesis of PCOS, identify the hub metabolites and investigate its associations with androgens. We applied GC-MS platform coupled with a correlation network approach to analyze follicular fluid samples from 32 PCOS patients without obesity and IR and 31 healthy women. Thirty significantly altered metabolites in PCOS patients were enriched in amino acid metabolism. l-Phenylalanine, l-tryptophan, pyroglutamic acid, l-tyrosine, l-leucine and l-valine were screened as hub metabolites in metabolic correlation network. Among them, increased l-tryptophan and l-tyrosine were altered hub metabolites, and they had a more significant impact on the metabolic change of PCOS. In addition, l-tryptophan and l-tyrosine were significantly positively associated with serum androgens levels in the PCOS. Our results suggest that disorders of amino acid metabolism, especially tryptophan and tyrosine metabolism, might play an important role in the development of PCOS in predisposed women without obesity and IR.

The utility of nuclear magnetic resonance spectroscopy in assisted reproduction

Infertility affects approximately 15-20% of individuals of reproductive age worldwide. Over the last 40 years, assisted reproductive technology (ART) has helped millions of childless couples. However, ART is limited by a low success rate and risk of multiple gestations. Devising methods for selecting the best gamete or embryo that increases the ART success rate and prevention of multiple gestation has become one of the key goals in ART today. Special emphasis has been placed on the development of non-invasive approaches, which do not require perturbing the embryonic cells, as the current morphology-based embryo selection approach has shortcomings in predicting the implantation potential of embryos. An observed association between embryo metabolism and viability has prompted researchers to develop metabolomics-based biomarkers. Nuclear magnetic resonance (NMR) spectroscopy provides a non-invasive approach for the metabolic profiling of tissues, gametes and embryos, with the key advantage of having a minimal sample preparation procedure. Using NMR spectroscopy, biologically important molecules can be identified and quantified in intact cells, extracts or secretomes. This, in turn, helps to map out the active metabolic pathways in a system. The present review covers the contribution of NMR spectroscopy in assisted reproduction at various stages of the process.

Protein Lysine Acetylation in Ovarian Granulosa Cells Affects Metabolic Homeostasis and Clinical Presentations of Women With Polycystic Ovary Syndrome

Polycystic ovary syndrome (PCOS) is one of the most common reproductive endocrine disorders accompanied by obvious metabolic abnormalities. Lower-quality oocytes and embryos are often found in PCOS women during assisted reproductive technology treatment. However, there is still no clarity about the mechanism of ovarian metabolic disorders and the impact on oocyte maturation in PCOS. The aim of this study was to understand the potential effect of the posttranslational modification on ovarian metabolic homeostasis and oocyte development potential in women with PCOS. A quantitative analysis of acetylated proteomics in ovarian granulosa cells of PCOS and control groups was carried out by mass spectrometry. There was widespread lysine acetylation of proteins, of which 265 proteins had increased levels of acetylation and 68 proteins had decreased levels of acetylation in the PCOS group. Most notably, differentially acetylated proteins were significantly enriched in the metabolic pathways of glycolysis, fatty acid degradation, TCA cycle, tryptophan metabolism, and branched-chain amino acid degradation. Acetyl-CoA acetyltransferase 1 (ACAT1) was an enzyme central to these metabolic pathways with increased acetylation level in the PCOS group, and there was a negative correlation of ACAT1 acetylation levels in PCOS granulosa cells with oocyte quality and embryo development efficiency in the clinic. Lysine acetylation changes of key enzymes in PCOS granulosa cells might attenuate their activities and alter metabolic homeostasis of follicular microenvironment for oocyte maturation and embryo development.

Relationship between the metabolic and lipid profile in follicular fluid of women undergoing in vitro fertilization

Among the follicular fluid (FF) components promoting the development of the oocyte are included glycoproteins, several fatty acids, and steroid hormones synthesized by the dominant follicle. For this, the analysis of the metabolites present in FF can determine the quality of the oocyte. FF composition is in part determined by local follicular metabolic processes and in part a plasma transudate. Since the causes of impaired fertility may be due to a metabolic imbalance, metabolomics is useful to identify low molecular weight metabolites. Oxidative stress is involved in human infertility and the use of metabolomics can be crucial to identify which other metabolites besides reactive oxygen species are involved in oxidative stress correlated to infertility. To obtain new information on the study of signaling molecules in FF, the knowledge of the lipid content will be important to improve information on the understanding of follicular development. The objective of this study is to identify (a) a metabolic profile and a lipid profile of FF in women undergoing in vitro fertilization and (b) to correlate the previous information obtained regarding adiponectin and oxidative stress with the metabolic and lipid profile obtained in the present study. As result, we found an increase in oxidative stress due to both an increase of androgens and an accumulation of lipids in the follicular environment and we suggest that this might be one of the causes of reduced fertility.

Metabolomic biomarkers of polycystic ovary syndrome related-obesity: a review of the literature

Background and objectives: Polycystic ovary syndrome (PCOS) displays a phenotype-dependent cardio-metabolic risk. By performing a systematic search of the literature, we aimed to summarize metabolomic signatures associated with obesity in PCOS women.

Data sources and study eligibility criteria: We conducted a comprehensive search including: Embase, PubMed, and Web of Science until 31st of May 2019. We used the terms: metabolomics and polycystic ovary syndrome. We excluded the following papers: animal studies, studies that included only lean PCOS women, reviews, meta-analyses, results of interventional studies, those that did not apply metabolomic techniques.

Results: The lipid signature in obese women with PCOS showed increased levels of free fatty acids (carnitine, adipic acid, linoleic acid, oleic acid) and lower levels of lysophosphatidylcholines and glycerolphosphocholine compared with non-obese PCOS women. Regarding carbohydrate metabolism, a decrease in citric and lactic acid levels characterized obese PCOS women. Decreased lactic acid in obese PCOS women suggests augmented insulin stimulated glucose muscle use in lean, but not in obese women. Considering amino acid metabolomic markers, valine, glycine, serine, threonine, isoleucine and lysine were higher in obese PCOS women. Patients with visceral obesity presented a diminished uptake of essential amino acids, BCAA, leucine and serine in the skeletal muscle. α-ketoglutarate was significantly higher in obese women with PCOS in comparison with lean women with PCOS, distinguishing these 2 subgroups of PCOS with high ‘predictive accuracy’.

Limitations: Overall, a small number of studies have focused on the impact of obesity on the metabolic fingerprints of PCOS women. There is need for properly controlled, high-quality studies.

Conclusions: There is compelling evidence of significant alterations in carbohydrate, lipid, and amino acid metabolism in women with PCOS and obesity. Metabolomics may identify new metabolic pathways involved in PCOS and improve our understanding of the complex relation between PCOS and obesity in order to personalize PCOS therapy.

Metabolomic Biomarkers in Gynecology: A Treasure Path or a False Path?

Omic-technologies (genomics, transcriptomics, proteomics and metabolomics) have become more important in current medical science. Among them, it is metabolomics that most accurately reflects the minor changes in body functioning, as it focuses on metabolome - the group of the metabolism products, both intermediate and end. Therefore, metabolomics is actively engaged in fundamental and clinical studies and search for potential biomarkers. The biomarker could be used in diagnostics, management and stratification of the patients, as well as in prognosing the outcomes. The good example is gynecology, since many gynecological diseases lack effective biomarkers. In the current review, we aimed to summarize the results of the studies, devoted to the search of potential metabolomic biomarkers for the most common gynecological diseases.

Metabolomic Insight into Polycystic Ovary Syndrome-An Overview

Searching for the mechanisms of the polycystic ovary syndrome (PCOS) pathophysiology has become a crucial aspect of research performed in the last decades. However, the pathogenesis of this complex and heterogeneous endocrinopathy remains unknown. Thus, there is a need to investigate the metabolic pathways, which could be involved in the pathophysiology of PCOS and to find the metabolic markers of this disorder. The application of metabolomics gives a promising insight into the research on PCOS. It is a valuable and rapidly expanding tool, enabling the discovery of novel metabolites, which may be the potential biomarkers of several metabolic and endocrine disorders. The utilization of this approach could also improve the process of diagnosis and therefore, make treatment more effective. This review article aims to summarize actual and meaningful metabolomic studies in PCOS and point to the potential biomarkers detected in serum, urine, and follicular fluid of the affected women.

Role of gut microbiota in the development of insulin resistance and the mechanism underlying polycystic ovary syndrome: a review

Polycystic ovary syndrome (PCOS) is a complex endocrine and metabolic disorder. Typically, it is characterized by hirsutism, hyperandrogenism, ovulatory dysfunction, menstrual disorders and infertility. To date, its pathogenesis remains unclear. However, insulin resistance (IR) is considered as the primary pathological basis for its reproductive dysfunction. On the other hand, a condition in which insulin is over-secreted is called hyperinsulinemia. IR/Hyperinsulinemia is associated with chronic inflammation, hormonal changes, follicular dysplasia, endometrial receptivity changes, and abortion or infertility. Additionally, it increases incidence of complications during pregnancy and has been associated with anxiety, depression, and other psychological disorders. Gut microbiota, the "second genome" acquired by the human body, can promote metabolism, immune response through interaction with the external environment. Gut microbiota dysbiosis can cause IR, which is closely linked to the occurrence of PCOS. This article reviewed recent findings on the roles of gut microbiota in the development of insulin resistance and the mechanism underlying polycystic ovary syndrome.

Non-invasive urinary metabolomics reveals metabolic profiling of polycystic ovary syndrome and its subtypes

Polycystic ovary syndrome (PCOS) is a heterogeneous endocrine disorder, which affects 4-10 % women of reproductive age. Though accumulating scientific evidence, its pathogenesis remains unclear. In the current study, metabolic profiling as well as diagnostic biomarkers for different phenotypes of PCOS was investigated using non-invasive urinary GCMS based metabolomics. A total of 371 subjects were recruited for the study. They constituted the following groups: healthy women, those with hyperandrogenism (HA), women with insulin-resistance (IR) in PCOS. Two cross-comparisons with PCOS were performed to characterize metabolic disturbances. A total of 23 differential metabolites were found. The altered metabolic pathways included glyoxylate and dicarboxylate metabolism, pentose and glucuronate interconversions, and citrate cycle and butanoate metabolism. For differential diagnosis, a panel consisting of 9 biomarkers was found from the comparison of PCOS from healthy subjects. The area under the receiver operating characteristic (ROC) curve (AUC) was 0.8461 in the discovery phase. Predictive value of 89.17 % was found in the validation set. Besides, a panel of 8 biomarkers was discovered from PCOS with HA vs IR. The AUC for 8-biomarker panel was 0.8363, and a panel of clinical markers (homeostasis model assessment-insulin resistance and free androgen index) had 0.8327 in AUC. While these metabolites combined with clinical markers reached 0.9065 in AUC from the discovery phase, and 93.18 % in predictive value from the validation set. The result showed that differences of small-molecule metabolites in urine may reflect underlying pathogenesis of PCOS and serve as biomarkers for complementary diagnosis of the different phenotypes of PCOS.

Serum metabolomics reveals metabolic profiling for women with hyperandrogenism and insulin resistance in polycystic ovary syndrome

INTRODUCTION

Polycystic ovary syndrome (PCOS) is a heterogeneous endocrine disorder. Hyperandrogenism (HA) and insulin resistance (IR) are two important pathogenic factors.

OBJECTIVE

We aimed to investigate the inherent disturbed metabolic profiles for women with HA or IR in PCOS as well as discover diagnostic biomarkers.

METHODS

A total of 286 subjects were recruited for the study. They constituted the following groups: healthy women (C), those with HA (B1), those with IR but not obese (B2) and obese women with IR (B3) in PCOS. Nine cross-comparisons with PCOS were performed to characterize metabolic disturbances. Serum metabolomic profiles were determined by gas chromatography-mass spectrometry.

RESULTS AND CONCLUSION

We found a total of 59 differential metabolites. 28 metabolites for B1 vs C, 32 for B2 vs C and 25 for B3 vs C were discovered. Among them, palmitic acid, cholesterol, myo-inositol, D-allose, 1,5-anhydro-D-sorbitol, 1-monopalmitin, 1-monostearin, glycerol 1-phosphate, malic acid and citric acid, were the common differential metabolites among B1 vs C, B2 vs C and B3 vs C, which related to biosynthesis of unsaturated fatty acids, citrate cycle etc. Besides, 9-biomarker panel can diagnose well between HA and IR in PCOS. They provided areas under the receiver operating characteristic curve of 0.8511 to 1.000 in the discovery phase, and predictive values of 90% to 92% in the validation set. The result indicated that the differential metabolites can reflect the underlying mechanism of PCOS and serve as biomarkers for complementary diagnosis of HA and IR in PCOS.

Coordinated Modulation of Energy Metabolism and Inflammation by Branched-Chain Amino Acids and Fatty Acids

As important metabolic substrates, branched-chain amino acids (BCAAs) and fatty acids (FAs) participate in many significant physiological processes, such as mitochondrial biogenesis, energy metabolism, and inflammation, along with intermediate metabolites generated in their catabolism. The increased levels of BCAAs and fatty acids can lead to mitochondrial dysfunction by altering mitochondrial biogenesis and adenosine triphosphate (ATP) production and interfering with glycolysis, fatty acid oxidation, the tricarboxylic acid cycle (TCA) cycle, and oxidative phosphorylation. BCAAs can directly activate the mammalian target of rapamycin (mTOR) signaling pathway to induce insulin resistance, or function together with fatty acids. In addition, elevated levels of BCAAs and fatty acids can activate the canonical nuclear factor-κB (NF-κB) signaling pathway and inflammasome and regulate mitochondrial dysfunction and metabolic disorders through upregulated inflammatory signals. This review provides a comprehensive summary of the mechanisms through which BCAAs and fatty acids modulate energy metabolism, insulin sensitivity, and inflammation synergistically.

Causal Effects of Genetically Determined Metabolites on Risk of Polycystic Ovary Syndrome: A Mendelian Randomization Study

Background: Polycystic ovary syndrome (PCOS) is a heterogeneous endocrine disorder that is influenced by both genetic and environmental factors. However, the etiology of PCOS remains unclear. Methods: We conducted a two-sample Mendelian randomization (MR) analysis to assess the causal effects of genetically determined metabolites (GDMs) on the risk of PCOS. We used summary level data of a genome-wide association study (GWAS) on 486 metabolites (n = 7,824) as exposure and a PCOS GWAS consisting of 4,138 cases and 20,129 controls as the outcome. Both datasets were obtained from publicly published databases. For each metabolite, a genetic instrumental variable was generated to assess the relationship between the metabolite and PCOS. For MR analysis, we primarily used the standard inverse variance weighted (IVW) method, while three additional methods-the MR-Egger, weighted median, and MR-PRESSO (pleiotropy residual sum and outlier) methods-were performed as sensitivity analyses. Results: Using genetic variants as predictors, we observed a robust relationship between epiandrosterone sulfate (EPIA-S) and PCOS (P_IVW = 0.0186, P_MR-Egger = 0.0111; P_{Weighted-median} = 0.0154, and P_MR-PRESSO = 0.0290). Similarly, 3-dehydrocarnitine, 4-hydroxyhippurate, hexadecanedioate, and β-hydroxyisovalerate may also have causal effects on PCOS development. Conclusions: We identified metabolites that might have causal effects on PCOS development. Our study emphasizes the role of genetic factors underlying the causal relationships between metabolites and PCOS and provides novel insights through the integration of metabolomics and genomics to better understand the mechanisms involved in human disease pathogenesis.

Guidelines for the use of flow cytometry and cell sorting in immunological studies (second edition)

These guidelines are a consensus work of a considerable number of members of the immunology and flow cytometry community. They provide the theory and key practical aspects of flow cytometry enabling immunologists to avoid the common errors that often undermine immunological data. Notably, there are comprehensive sections of all major immune cell types with helpful Tables detailing phenotypes in murine and human cells. The latest flow cytometry techniques and applications are also described, featuring examples of the data that can be generated and, importantly, how the data can be analysed. Furthermore, there are sections detailing tips, tricks and pitfalls to avoid, all written and peer-reviewed by leading experts in the field, making this an essential research companion.

Changes in whole metabolites after exenatide treatment in overweight/obese polycystic ovary syndrome patients

OBJECTIVE

Exenatide is a new agent for diabetes therapy, and its use in polycystic ovary syndrome (PCOS) has gradually increased; however, the clinical benefit and metabolic improvement need further evidence. This research aimed to study the changes in whole metabolites before and after exenatide treatment in overweight/obese PCOS patients to gain a better understanding of exenatide for the treatment of PCOS.

METHODS

Sixty-seven women, including 32 with PCOS and 35 age-matched controls, were recruited. The metabolite changes were detected with nontargeted gas chromatography-tandem mass spectrometry (NTGC-MS) before and after exenatide treatment, and changes in clinical biochemical characteristics were also observed.

RESULTS

A total of 62 metabolites were differentially expressed between the healthy and PCOS groups, and 31 differentially expressed metabolites were detected before and after exenatide treatment. Abnormal lipid metabolism and amino acid metabolism were the main metabolic disorders. Exenatide improved lipid and amino acid metabolism, especially amino acid metabolites. Three types of branched-chain amino acids (valine, leucine and isoleucine), two types of aromatic amino acids (phenylalanine and tyrosine) and lysine are important potential metabolites for the therapeutic efficacy of exenatide. Many abnormal metabolic disorders are related to insulin resistance, oxidative stress and even ovulatory dysfunction. Moreover, in this small sample clinical study, we also found that exenatide improved insulin sensitivity, reduced body weight and improved glycolipid metabolism in PCOS.

CONCLUSIONS

NTGC-MS-based metabolic pathway analysis revealed that exenatide has a beneficial effect on overweight/obese PCOS patients by regulating metabolic disorders, especially amino acid disorders.

Lipidomics biomarkers in women with polycystic ovary syndrome (PCOS) using ultra-high performance liquid chromatography-quadrupole time of flight electrospray in a positive ionization mode mass spectrometry

Polycystic ovary syndrome (PCOS), characterized by oligo-anovulation and androgen excess is considered a high-risk condition for metabolic disorders. Herein, untargeted metabolomics analysis was applied to women with PCOS, aiming to provide deeper insights into lipidomics biomarkers signature of PCOS, for better diagnosis and management. This was a cross-sectional study in which 15 Caucasian women with PCOS and 15 Caucasian healthy, age-matched women were enrolled. Lipidomics analysis was performed using Ultra-High Performance Liquid Chromatography-Quadrupole Time of Flight Electrospray Mass Spectrometry. Partial Least Squares Discriminant Analysis retrieved the most important discriminative metabolites. Significantly increased levels of triacylglycerol (18:2/18:2/0-18:0) in addition to cholestane-3beta, 5alpha, 6beta-triol (18:0/0:0) and cholestane-5alpha (18:1/0:0) appeared as valuable variables to differentiate subjects with PCOS from controls. Acyl-carnitine 2-hydroxylauroylcarnitine was significantly elevated in PCOS in opposition to decreased phosphocholines metabolites (18:1/18:4, 18:3/18:2), to suggest a metabolic pattern linked to lipid peroxidation. A high fat intake or reduced fat energy consumption during nighttime due to diminished ability to switch to lipid oxidation during fasting time possibly contribute to hypertriglyceridemia found in PCOS. Furthermore, inflammatory mediators including metabolites of the prostaglandin (PG) E2 pathway and oxo-leukotrienes (LT) were increased in patients with PCOS. Potential lipidomics biomarkers were identified that could stratify between women with PCOS and healthy controls. The results show particular alterations in acylglycerols, PGs and LTs and phosphocholines and carnitine metabolites. The lipidomics profiles of PCOS indicate a higher risk of developing metabolic diseases.

Identification of potential metabolic biomarkers of polycystic ovary syndrome in follicular fluid by SWATH mass spectrometry

BACKGROUND

Polycystic ovary syndrome (PCOS) is a complex disorder associated with multiple metabolic disturbance, including defective glucose metabolism and insulin resistance. The altered metabolites caused by the related metabolic disturbance may affect ovarian follicles, which can be reflected in follicular fluid composition. The aim of this study is to investigate follicular fluid metabolic profiles in women with PCOS using an advanced sequential window acquisition of all theoretical fragment-ion spectra (SWATH) mass spectrometry.

MATERIALS AND METHODS

Nineteen women with PCOS and twenty-one healthy controls undergoing IVF/ET were recruited, and their follicular fluid samples were collected for metabolomic study. Follicular fluid metabolic profiles, including steroid hormones, free fatty acids, bioactive lipids, and amino acids were analyzed using the principal component analysis (PCA) and partial least squares to latent structure-discriminant analysis (PLS-DA) model.

RESULTS

Levels of free fatty acids, 3-hydroxynonanoyl carnitine and eicosapentaenoic acid were significantly increased (P < 0.05), whereas those of bioactive lipids, lysophosphatidylcholines (LysoPC) (16:0), phytosphingosine, LysoPC (14:0) and LysoPC (18:0) were significantly decreased in women with PCOS (P < 0.05). Additionally, levels of steroid hormone deoxycorticosterone and two amino acids, phenylalanine and leucine were higher in the PCOS patients (P < 0.05).

CONCLUSION

Women with PCOS display unique metabolic profiles in their follicular fluid, and this data may provide us with important biochemical information and metabolic signatures that enable a better understanding of the pathogenesis of PCOS.

Metabolomic Analysis Identifies Alterations of Amino Acid Metabolome Signatures in the Postmortem Brain of Alzheimer's Disease

Despite significant advances in neuroscience research over the past several decades, the exact cause of AD has not yet fully understood. The metabolic hypothesis as well as the amyloid and tau hypotheses have been proposed to be associated with AD pathogenesis. In order to identify metabolome signatures from the postmortem brains of sporadic AD patients and control subjects, we performed ultra performance liquid chromatography coupled with linear ion trap-Orbitrap mass spectrometer (UPLC-LTQ-Orbitrap-MS). Not only our study identified new metabolome signatures but also verified previously known metabolome profiles in the brain. Statistical modeling of the analytical data and validation of the structural assignments discovered metabolic biomarkers associated with the AD pathogenesis. Interestingly, hypotaurin, myo-inositol and oxo-proline levels were markedly elevated in AD while lutamate and N-acetyl-aspartate were decreased in the postmortem brain tissue of AD patients. In addition, neurosteroid level such as cortisol was significantly increased in AD. Together, our data indicate that impaired amino acid metabolism is associated with AD pathogenesis and the altered amino acid signatures can be useful diagnostic biomarkers of AD. Thus, modulation of amino acid metabolism may be a possible therapeutic approach to treat AD.

Amino acid and fatty acid metabolomic profile during fasting and hyperinsulinemia in girls with polycystic ovarian syndrome

Polycystic ovarian syndrome (PCOS) is associated with insulin resistance (IR) and altered muscle mitochondrial oxidative phosphorylation. IR in adults with obesity and diabetes is associated with changes in amino acid, free fatty acid (FFA), and mitochondrial acylcarnitine (AC) metabolism. We sought to determine whether these metabolites are associated with IR and/or androgens in youth-onset PCOS. We enrolled obese girls with PCOS [ n = 15, 14.5 yr (SD 1.6), %BMI 98.5 (SD 1.0)] and without PCOS [ n = 6, 13.2 yr (SD 1.2), %BMI 98.0 (SD 1.1)]. Insulin sensitivity was assessed by hyperinsulinemic euglycemic clamp. Untargeted metabolomics of plasma was performed while fasting and during hyperinsulinemia. Fasting arginine, glutamine, histidine, lysine, phenylalanine, and tyrosine were higher ( P < 0.04 for all but P < 0.001 for valine), as were glutamine and histidine during hyperinsulinemia ( P < 0.03). Higher valine during hyperinsulinemia was associated with IR ( r = 0.59, P = 0.006). Surprisingly, end-clamp AC C4 was lower in PCOS, and lower C4 was associated with IR ( r = -0.44, P = 0.04). End-clamp FFAs of C14:0, C16:1, and C18:1 were higher in PCOS girls, and C16:1 and C18:1 strongly associated with IR ( r = 0.73 and 0.53, P < 0.01). Free androgen index related negatively to short-, medium-, and long-chain AC ( r = -0.41 to -0.71, P < 0.01) but not FFA or amino acids. Obese girls with PCOS have a distinct metabolic signature during fasting and hyperinsulinemia. As in diabetes, IR related to valine and FFAs, with an unexpected relationship with AC C4, suggesting unique metabolism in obese girls with PCOS.

Current Progress of Lipid Analysis in Metabolic Diseases by Mass Spectrometry Methods

BACKGROUND

Obesity, insulin resistance, diabetes, and metabolic syndrome are associated with lipid alterations, and they affect the risk of long-term cardiovascular disease. A reliable analytical instrument to detect changes in the composition or structures of lipids and the tools allowing to connect changes in a specific group of lipids with a specific disease and its progress, is constantly lacking. Lipidomics is a new field of medicine based on the research and identification of lipids and lipid metabolites present in human organism. The primary aim of lipidomics is to search for new biomarkers of different diseases, mainly civilization diseases.

OBJECTIVE

We aimed to review studies reporting the application of mass spectrometry for lipid analysis in metabolic diseases.

METHOD

Following an extensive search of peer-reviewed articles on the mass spectrometry analysis of lipids the literature has been discussed in this review article.

RESULTS

The lipid group contains around 1.7 million species; they are totally different, in terms of the length of aliphatic chain, amount of rings, additional functional groups. Some of them are so complex that their complex analyses are a challenge for analysts. Their qualitative and quantitative analysis of is based mainly on mass spectrometry.

CONCLUSION

Mass spectrometry techniques are excellent tools for lipid profiling in complex biological samples and the combination with multivariate statistical analysis enables the identification of potential diagnostic biomarkers.

Metabolomic change due to combined treatment with myo-inositol, D-chiro-inositol and glucomannan in polycystic ovarian syndrome patients: a pilot study

Background

Polycystic ovarian syndrome (PCOS) is a highly variable syndrome and one of the most common female endocrine disorders. Although the association inositols-glucomannan may represent a good therapeutic strategy in the treatment of PCOS women with insulin resistance, the effect of inositols on the metabolomic profile of these women has not been described yet.

Results

Fifteen PCOS-patients and 15 controls were enrolled. Patients were treated with myo-inositol (1.75 g/day), D-chiro-inositol (0.25 g/day) and glucomannan (4 g/day) for 3 months. Blood concentrations of glucose, insulin, triglycerides and cholesterol, and ovary volumes and antral follicles count, as well as metabolomic profiles, were evaluated for control subjects and for cases before and after treatment.

PCOS-patients had higher BMI compared with Controls, BMI decreased significantly after 3 months of treatment although it remained significantly higher compared to controls. 3-methyl-1-hydroxybutyl-thiamine-diphosphate, valine, phenylalanine, ketoisocapric, linoleic, lactic, glyceric, citric and palmitic acid, glucose, glutamine, creatinine, arginine, choline and tocopherol emerged as the most relevant metabolites for distinguishing cases from controls.

Conclusion

Our pilot study has identified a complex network of serum molecules that appear to be correlated with PCOS, and with a combined treatment with inositols and glucomannan.

Trial registration

ClinicalTial.gov, NCT03608813. Registered 1st August 2018 - Retrospectively registered, .

Electronic supplementary material

The online version of this article (10.1186/s13048-019-0500-x) contains supplementary material, which is available to authorized users.

Alterations of Sphingolipid Metabolism in Different Types of Polycystic Ovary Syndrome

The roles of sphingolipids in polycystic ovary syndrome (PCOS) are still unknown. This study aimed to investigate the sphingolipid characteristics for different types of PCOS using liquid chromatography-mass spectrometry (LC-MS). A total of 107 women with PCOS and 37 healthy women as normal controls were studied. PCOS patients were further classified into non-obesity with insulin resistance (IR) (NOIR), obesity with IR (OIR), and non-obesity and non-IR (NIR) subgroups. A total of 87 serum sphingolipids, including 9 sphingosines, 3 sphinganines, 1 sphingosine-1-phosphate (S1P), 19 ceramides (Cers), 1 ceramide-1-phosphate, 44 sphingomyelins (SMs), 4 hexosylceramides, and 6 lactosylceramides (LacCers) were analyzed using an improved sphingolipidomic approach based on LC-MS. Notable elevations in the levels of S1P, Cer, and SM were observed in PCOS patients when compared with healthy women, and SM species with long saturated acyl chains showed potential as novel biomarkers of PCOS. In addition, the level of LacCer was only elevated in NIR, and there was almost no change in NOIR and OIR. This study is the first to report the comprehensive sphingolipidomic profiling of different subgroups of PCOS with or without IR or obesity and suggests that serum sphingolipids might be useful as diagnostic biomarkers for different types of PCOS.

Identification of the metabolic fingerprints in women with polycystic ovary syndrome using the multiplatform metabolomics technique

In addition to chronic anovulation and clinical signs of hyperandrogenism women with polycystic ovary syndrome (PCOS) are insulin resistant and therefore, develop central obesity with its long term consequences such as dyslipidaemia, hypertension, atherosclerosis and type 2 diabetes mellitus (T2DM), which all lead to the development of cardiovascular disease (CVD). Due to the polysymptomatic nature of this syndrome and lack of consensus on its diagnostic criteria there is a strong need of finding a reliable biochemical or molecular marker, which would facilitate making the accurate diagnosis of PCOS. Therefore, the aim of our study was to perform a metabolomics analysis with the use of two complementary techniques: gas chromatography and liquid chromatography coupled with mass spectrometry, of the serum samples from women with PCOS (n = 30) and to compare them with healthy age and BMI matched controls (n = 30). Obtained results were subjected to one-dimensional statistical analysis (student's t-test or its non-parametric equivalent U Mann-Whitney test) and multivariate statistical analysis (the principal component analysis [PCA], variable importance into projection [VIP] and selectivity ratio [SR]). The results of our study showed that women with PCOS are characterised by metabolic disorders of the amino acids, carbohydrates, steroid hormones, lipids and purines. Compared to control subjects, women with PCOS had increased serum levels of phospholipids, aromatic amino acids, organic acids, hormones and sphinganine and decreased total cholesterol. Among the identified compounds, total cholesterol, phenylalanine and dehydroepiandrosterone sulfate, uric and lactic acid were the compounds with the strongest discriminating power.

Serum metabolomics analysis of patients with polycystic ovary syndrome by mass spectrometry

Polycystic ovary syndrome (PCOS) is a set of symptoms caused by elevated androgens (male hormones) in females. PCOS is the most common endocrine disorder among women between 18 and 44 years. Currently, the pathogenesis of PCOS remains unclear. Liquid chromatography-mass spectrometry (LC/MS)-based metabolomics is becoming more and more useful for medical research, especially in revealing the mechanism of the disease. The aim of this study was to investigate the difference of serum metabolic profiles in patients with PCOS and healthy control to better understand the mechanism of this disease. Ten patients with PCOS and 10 healthy people were recruited for this study. The serum samples were collected for LC/MS analysis. Multivariate statistical analysis was performed to discover and identify the potential biomarkers. Six biomarkers were found and identified. The biomarkers belonged to different metabolic pathway including lipid metabolism, carnitine metabolism, androgen metabolism, and bile acid metabolism. Those biomarkers also played different roles in disease progression. Metabolomics is a powerful tool used in research of the mechanism involved in this disease to provide useful information for better understanding of PCOS.

Metabolomics of Dynamic Changes in Insulin Resistance Before and After Exercise in PCOS

Background: Plasma elevated levels of branched chain amino acids (BCAA) and aromatic amino acids (AAA) have been associated with obesity and insulin resistance, but their relationship to stimulated insulin resistance (IR) in PCOS and in response to exercise is unknown. Indeed, it is unknown whether the mechanism of IR in PCOS is mediated through changes in the metabolome. Methods: Twelve women with polycystic ovary syndrome (PCOS) and ten age and body mass index matched controls completed an 8 week supervised exercise program at 60% maximal oxygen consumption. Before and after the exercise program, all participants underwent maximal IR stimulation with intralipid infusions followed by insulin sensitivity (IS) measurement by hyperinsulinaemic euglycaemic clamps. Amino acid profiles and metabolites were taken at baseline and at maximal insulin resistance stimulation before and after the exercise program. Results: At baseline, PCOS subjects showed increased leucine/isoleucine, glutamate, methionine, ornithine, phenylalanine, tyrosine and proline (p < 0.05) that, following exercise, did not differ from controls. While compering within the groups, no significant changes in the amino acid levels before and after exercise were observed. Exercise improved VO2 max (p < 0.01) but did not alter weight. Amino acid profiles were unaffected by an acute increase in IR induced by the lipid infusion. IS was lower in PCOS (p < 0.001) and was further decreased by the lipid infusion in both PCOS and controls. Although, exercise improved IS in both PCOS and in controls, the IS remained compromised in PCOS. Conclusion: The baseline amino acid profile in PCOS reflected that seen in obese subjects and differed to controls. After exercise, and despite no change in weight in either group, there were no differences in the amino acid profile between PCOS and controls. This shows that exercise may normalize the amino acid metabolome, irrespective of weight. ISRCTN number: ISRCTN42448814.

Genetics and genomics of reproductive disorders in Canadian Holstein cattle

In Canada, reproductive disorders known to affect the profitability of dairy cattle herds have been recorded by producers on a voluntary basis since 2007. Previous studies have shown the feasibility of using producer-recorded health data for genetic evaluations. Despite low heritability estimates and limited availability of phenotypic information, sufficient genetic variation has been observed for those traits to indicate that genetic progress, although slow, can be achieved. Pedigree- and genomic-based analyses were performed on producer-recorded health data of reproductive disorders, including retained placenta (RETP), metritis (METR), and cystic ovaries (CYST) using traditional BLUP and single-step genomic BLUP. Genome-wide association studies and functional analyses were carried out to unravel significant genomic regions and biological pathways, and to better understand the genetic mechanisms underlying RETP, METR, and CYST. Heritability estimates (posterior standard deviation in parentheses) were 0.02 (0.003), 0.01 (0.004), and 0.02 (0.003) for CYST, METR, and RETP, respectively. A moderate to strong genetic correlation of 0.69 (0.102) was found between METR and RETP. Averaged over all traits, sire proof reliabilities increased by approximately 11 percentage points with the incorporation of genomic data using a multiple-trait linear model. Biological pathways and associated genes underlying the studied traits were identified and will contribute to a better understanding of the biology of these 3 health disorders in dairy cattle.

UPLC/Q‑TOF‑MS based plasma metabolomics and clinical characteristics of polycystic ovarian syndrome

The present study aimed to develop novel diagnostic methods for polycystic ovarian syndrome (PCOS) by screening and identifying specific PCOS‑associated metabolic markers using plasma metabolomics. Ultra‑performance liquid chromatography/quadrapole‑time of flight‑mass spectrometry was adopted to establish the plasma metabolic fingerprint of 49 patients and 50 normal controls, in order to screen the potential metabolic markers. In addition, these markers were integrated with the clinical indexes, followed by focused analysis to obtain diagnostic markers. The present results demonstrated that not only was the concentration of palmitoyl sphingomyelin in plasma of patients with PCOS significantly increased; however, a statistically significant difference between the two PCOS subgroups was additionally demonstrated. At the same time, the concentrations of cyclic guanosine monophosphate (cGMP) and dehydroepiandrosterone sulphate in the plasma of patients of the subgroup 1 were significantly elevated. These markers were additionally integrated with the clinical index number of follicles in the left ovary and high‑density lipoprotein (HDL‑C), followed by receiver operating characteristic curve analysis, which demonstrated a diagnostic accuracy of ~90% in the control and the two subgroups. The integrated marker system consisting of palmitoyl sphingomyelin, cGMP and androsterone sulfate, as well as the number of left follicles and HDL‑C may be used for the accurate diagnosis and classification of PCOS. These results confirmed that the abnormalities in hormone metabolism and lipid metabolism disorder were primarily involved in the onset of PCOS.

Association between the prevalence of hyperuricemia and reproductive hormones in polycystic ovary syndrome

BACKGROUND

The prevalecne of hyperuricemia in polycystic ovary syndrome (PCOS) is still uncertain. We aimed to investigate the prevalence of hyperuricemia in PCOS and to determine the influence of reproductive hormones on uric acid concentration.

METHODS

This retrospective cross-sectional study was performed at a large reproductive medicine center. Between March 2007 and October 2016, a total of 1,183 women with PCOS and 10,772 women without PCOS were included. PCOS was diagnosed according to the Rotterdam criteria. Anthropometric parameters, blood pressure, uric acid, reproductive hormones, glucose and lipids were measured in all subjects.

RESULTS

The serum uric acid (SUA) level was higher in women with PCOS than in women without PCOS. The prevalence of hyperuricemia in women with PCOS (25.48%) was significantly higher than that in women without PCOS (8.74%). Analysis stratified for age and body mass index (BMI) showed that both the SUA level and the prevalence of hyperuricemia were higher in women with PCOS of different age and BMI groups than in women without PCOS. After adjusting for age, BMI and estimated glomerular filtration rate (eGFR), logistic regression analysis revealed that the luteinizing/follicle-stimulating hormone (LH/FSH) ratio (odds ratio (OR) = 1.20, 95% CI = 1.01-1.43) and testosterone level (OR = 1.56, 95% CI = 1.27-1.90) were positively associated with the prevalence of hyperuricemia in females with PCOS.

CONCLUSIONS

The serum uric acid (SUA) level and the prevalence of hyperuricemia markedly increased in women with PCOS. The testosterone level was positively associated with the SUA level and the prevalence of hyperuricemia in females with PCOS.

Menstrual cycle rhythmicity: metabolic patterns in healthy women

The menstrual cycle is an essential life rhythm governed by interacting levels of progesterone, estradiol, follicular stimulating, and luteinizing hormones. To study metabolic changes, biofluids were collected at four timepoints in the menstrual cycle from 34 healthy, premenopausal women. Serum hormones, urinary luteinizing hormone and self-reported menstrual cycle timing were used for a 5-phase cycle classification. Plasma and urine were analyzed using LC-MS and GC-MS for metabolomics and lipidomics; serum for clinical chemistries; and plasma for B vitamins using HPLC-FLD. Of 397 metabolites and micronutrients tested, 208 were significantly (p < 0.05) changed and 71 reached the FDR 0.20 threshold showing rhythmicity in neurotransmitter precursors, glutathione metabolism, the urea cycle, 4-pyridoxic acid, and 25-OH vitamin D. In total, 39 amino acids and derivatives and 18 lipid species decreased (FDR < 0.20) in the luteal phase, possibly indicative of an anabolic state during the progesterone peak and recovery during menstruation and the follicular phase. The reduced metabolite levels observed may represent a time of vulnerability to hormone related health issues such as PMS and PMDD, in the setting of a healthy, rhythmic state. These results provide a foundation for further research on cyclic differences in nutrient-related metabolites and may form the basis of novel nutrition strategies for women.

Identification of Potential Biomarkers for Urine Metabolomics of Polycystic Ovary Syndrome Based on Gas Chromatography-Mass Spectrometry

Background:

Polycystic ovary syndrome (PCOS) is a complex endocrine and metabolic disorder, and it's diagnosis is difficult. The aim of this study was to investigate the metabolic profiles of PCOS patients by analyzing urine samples and identify useful biomarkers for diagnosis of PCOS.

Methods:

This study was carried out in the Department of Obstetrics and Gynecology of the Maternal and Child Health Hospital of Hunan Province from December 2014 to July 2016. In this study, the urine samples of 21 women with PCOS and 16 healthy controls were assessed through gas chromatography-mass spectrometry to investigate the urine metabolite characteristics of PCOS and identify useful biomarkers for the diagnosis of this disorder. The Student's t-test and rank sum test were applied to validate the statistical significance of the between the two groups.

Results:

In total, 35 urine metabolites were found to be significantly different between the PCOS patients and the controls. In particular, a significant increase in the levels of lactose (10.01 [0,13.99] mmol/mol creatinine vs. 2.35 [0.16, 3.26] mmol/mol creatinine, P = 0.042), stearic acid (2.35 [1.47, 3.14] mmol/mol creatinine vs. 0.05 [0, 0.14] mmol/mol creatinine, P < 0.001), and palmitic acid (2.13 [1.07, 2.79] mmol/mol creatinine vs. 0 [0, 0] mmol/mol creatinine, P < 0.001) and a decrease in the levels of succinic acid (0 [0, 0] mmol/mol creatinine vs. 38.94 [4.16, 51.30] mmol/mol creatinine, P < 0.001) were found in the PCOS patients compared with the controls. It was possible to cluster the PCOS patients and the healthy controls into two distinct regions based on a principal component analysis model. Of the differentially expressed metabolites, four compounds, including stearic acid, palmitic acid, benzoylglycine, and threonine, were selected as potential biomarkers.

Conclusions:

This study offers new insight into the pathogenesis of PCOS, and the discriminating urine metabolites may provide a prospect for the diagnosis of PCOS.